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Model Selection and Testing of Conditional and Stochastic Volatility Models

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  • Caporin, M.
  • McAleer, M.J.

Abstract

This paper focuses on the selection and comparison of alternative non-nested volatility models. We review the traditional in-sample methods commonly applied in the volatility framework, namely diagnostic checking procedures, information criteria, and conditions for the existence of moments and asymptotic theory, as well as the out-of-sample model selection approaches, such as mean squared error and Model Confidence Set approaches. The paper develops some innovative loss functions which are based on Value-at-Risk forecasts. Finally, we present an empirical application based on simple univariate volatility models, namely GARCH, GJR, EGARCH, and Stochastic Volatility that are widely used to capture asymmetry and leverage.

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File URL: http://hdl.handle.net/1765/20940
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Bibliographic Info

Paper provided by Erasmus University Rotterdam, Econometric Institute in its series Econometric Institute Report with number EI 2010-57.

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Date of creation: 12 Oct 2010
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Handle: RePEc:dgr:eureir:1765020940

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Web page: http://www.few.eur.nl/few

Related research

Keywords: asymmetry; leverage; model confidence set; non-nested models; volatility model comparison; volatility model selection; Value-at-Risk forecasts;

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